Kuaishou

Kuaishou is a large-scale short-video recommendation system dataset used to evaluate the effectiveness of generative retrieval methods in producing high-quality candidate recommendations under strict latency constraints.

Papers using Kuaishou (7)

LLM-Aligned Geographic Item Tokenization for Local-Life Recommendation2025Breaking the Likelihood Trap: Consistent Generative Recommendation with Graph-structured Model2025MARS: Modality-Aligned Retrieval for Sequence Augmented CTR Prediction2025OneRec-V2 Technical Report2025Stratified Expert Cloning for Retention-Aware Recommendation at Scale2025Feature-aware Diversified Re-ranking with Disentangled Representations for Relevant Recommendation2022 · 51 citesDisentangled Causal Embedding With Contrastive Learning For Recommender System2023 · 20 cites